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duganth

py-ynab-mcp

by duganth

create_scheduled_transaction

Create a scheduled recurring transaction in YNAB by specifying account, amount, date, and frequency. Supports daily, weekly, monthly, yearly schedules with optional dry-run validation.

Instructions

Create a scheduled (recurring) transaction in YNAB.

Args: account_id: Account UUID. amount: Dollar amount ("-42.50" for outflow, "100.00" for inflow). date: First occurrence date (YYYY-MM-DD). frequency: Recurrence frequency. Only single-word values work via the YNAB API: "never", "daily", "weekly", "monthly", "yearly". Multi-word camelCase values (everyOtherWeek, twiceAMonth, etc.) are documented but rejected by YNAB's own backend — set those manually in the YNAB UI. payee_name: Payee name. category_id: Category UUID. memo: Transaction memo. flag_color: Flag color. budget_id: Budget ID. Defaults to last-used budget. dry_run: Validate and preview without creating.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYes
memoNo
amountYes
dry_runNo
budget_idNo
frequencyYes
account_idYes
flag_colorNo
payee_nameNo
category_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses important behaviors: frequency values limitation (multi-word rejected by YNAB backend), dry_run parameter for preview, and default budget_id. It could mention if changes are reversible or auth requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a header and bullet points. It is slightly long but every sentence adds value. No redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 10 parameters, 0% schema coverage, and no annotations, the description covers all parameters, explains behavior, and mentions a dry run feature. Output schema exists, so return values need not be described. Complete for usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It provides detailed explanations for all 10 parameters, including amount format ('-42.50' for outflow), date format (YYYY-MM-DD), frequency caveat, and default for budget_id. This adds significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Create a scheduled (recurring) transaction in YNAB,' which is a specific verb and resource. It distinguishes from siblings like create_transaction by specifying 'recurring.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for recurring transactions but does not explicitly state when to use this tool over alternatives like create_transaction or when not to use it. No exclusions or alternatives are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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